package com.heima.kafka.sample;

import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.streams.KafkaStreams;
import org.apache.kafka.streams.KeyValue;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.StreamsConfig;
import org.apache.kafka.streams.kstream.*;

import java.time.Duration;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
import java.util.Properties;

/**
 * 流式处理
 */
public class KafkaStreamQuickStart {

    public static void main(String[] args) {

        //kafka的配置信息
        Properties properties = new Properties();
        properties.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.200.130:9092");
        properties.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
        properties.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass());
        properties.put(StreamsConfig.APPLICATION_ID_CONFIG, "streams-quickstart");

        //stream 构建器
        StreamsBuilder streamsBuilder = new StreamsBuilder();


        //流式计算
        streamProcessor(streamsBuilder);


        //创建kafkaStream对象
        KafkaStreams kafkaStreams = new KafkaStreams(streamsBuilder.build(), properties);
        //开始流式计算
        kafkaStreams.start();
    }

    /**
     * 流式计算
     * 消息内容： hello kafka
     *
     * @param streamsBuilder
     */
    private static void streamProcessor(StreamsBuilder streamsBuilder) {

        //创建KStream对象，同时从指定哪个topic中接收消息
        KStream<String, String> stream = streamsBuilder.stream("itcast-topic-input");

        /**
         * 处理消息的value值
         */
        stream
                .flatMapValues(new ValueMapper<String, Iterable<String>>() {
                    @Override
                    public Iterable<String> apply(String value) {
                        return Arrays.asList(value.split(" "));
                    }
                })
                //按照value进行聚合处理
                .groupBy(new KeyValueMapper<String, String, Object>() {
                    @Override
                    public Object apply(String key, String value) {
                        return value;
                    }
                })
                //时间窗口
                .windowedBy(TimeWindows.of(Duration.ofSeconds(10))
                )
                //统计单词个数
                .count()
                //转化为KStream
                .toStream()
                .map((key,value)->{
                    String s = key.toString().split("@")[0].substring(1);
                    System.out.println("Key: "+s+",value: "+value);
                    return new KeyValue<>(key.toString(),value.toString());
                }).to("itcast-topic-out");
    }
}
